Abstract
Distributed self-adaptive systems are on the verge of becoming an essential part of personal life. They consist of connected subsystems, which work together to serve a higher goal. The highly distributed and self-organizing nature of the resulting system poses the need for runtime management. Here, a particular problem of interest is to determine an optimal approach for knowledge exchange between the constituent systems. In the context of multi-agent systems, a lot of theoretical work investigating this problem has been conducted over the past decades, showing that different approaches are optimal in different situations. Thus, to actually build such systems, the insights from existing theoretical approaches need to be validated against concrete situations. For this purpose, we present a simulation platform to test different knowledge exchange strategies in a test scenario. We used the open source context simulator Siafu as a basis for our simulation. The described platform enables the user to easily specify new types of constituent systems and their communication mechanisms. Moreover, the platform offers several integrated metrics, which are easily extensible. We evaluate the applicability of the platform using three different collaboration scenarios.
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References
Bäumer, D., Riehle, D., Siberski, W., Wulf, M.: The role-object pattern. In: Proceedings of the 4th Pattern Languages of Programming Conference (PLoP) (1997)
Behrisch, M., Bieker, L., Erdmann, J., Krajzewicz, D.: SUMO-simulation of urban mobility. In: The Third International Conference on Advances in System Simulation (SIMUL), Barcelona, Spain (2011)
Bellifemine, F., Poggi, A., Rimassa, G.: JADE-A FIPA-compliant agent framework. In: Proceedings of PAAM, London, vol. 99, p. 33 (1999)
Broekstra, J., Kampman, A., van Harmelen, F.: Sesame: a generic architecture for storing and querying RDF and RDF schema. In: Horrocks, I., Hendler, J. (eds.) ISWC 2002. LNCS, vol. 2342, pp. 54–68. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-48005-6_7
Bures, T., Gerostathopoulos, I., Hnetynka, P., Keznikl, J., Kit, M., Plasil, F.: DEECO: an ensemble-based component system. In: Proceedings of the 16th International ACM Sigsoft Symposium on Component-based Software Engineering, CBSE, pp. 81–90. ACM, New York (2013)
Calinescu, R., Gerasimou, S., Banks, A.: Self-adaptive software with decentralised control loops. In: Egyed, A., Schaefer, I. (eds.) FASE 2015. LNCS, vol. 9033, pp. 235–251. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46675-9_16
Gamma, E.: Design Patterns: Elements of Reusable Object-Oriented Software. Pearson Education India, Bengaluru (1995)
Götz, S., Gerostathopoulos, I., Krikava, F., Shahzada, A., Spalazzese, R.: Adaptive exchange of distributed partial models@run.time for highly dynamic systems. In: Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems. IEEE (2015)
Howden, N., Rönnquist, R., Hodgson, A., Lucas, A.: Jack intelligent agents-summary of an agent infrastructure. In: 5th International conference on autonomous agents (2001)
Kim, J., Sridhara, V., Bohacek, S.: Realistic mobility simulation of urban mesh networks. Ad Hoc Netw. 7(2), 411–430 (2009)
Martin, M., Nurmi, P.: A generic large scale simulator for ubiquitous computing. In: Third Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous), San Jose. IEEE, July 2006
Palomares, I., Killough, R., Bauters, K., Liu, W., Hong, J.: A collaborative multiagent framework based on online risk-aware planning and decision-making. In: 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI), pp. 25–32, November 2016
Poslad, S.: Specifying protocols for multi-agent systems interaction. ACM Trans. Auton. Adapt. Syst. 2(4), 15 (2007)
Salehie, M., Tahvildari, L.: Self-adaptive software: landscape and research challenges. ACM Trans. Auton. Adapt. Syst. 4(2), 14:1–14:42 (2009)
Sonnessa, M.: JAS: Java agent-based simulation library, an open framework for algorithm-intensive simulations. In: Industry and Labor Dynamics: The Agent-Based Computational Economics Approach. World Scientific, Singapore (2004)
Varga, A., Hornig, R.: An overview of the OMNeT++ simulation environment. In: Proceedings of the 1st International Conference on Simulation Tools and Techniques for Communications, Networks and Systems & Workshops, Simutools, Brussels, pp. 60:1–60:10. ICST (2008)
Werner, C.: Adaptive knowledge exchange with distributed partial models@run.time. Master’s thesis, Technische Universität Dresden, January 2016
Acknowledgments
This work has been funded by the German Research Foundation within the Collaborative Research Center 912 “Highly Adaptive Energy-Efficient Computing” and within the Research Training Group “Role-based Software Infrastructures for continuous-context-sensitive Systems” (GRK 1907).
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Werner, C., Götz, S., Aßmann, U. (2018). A Simulation Framework to Analyze Knowledge Exchange Strategies in Distributed Self-adaptive Systems. In: Seidl, M., Zschaler, S. (eds) Software Technologies: Applications and Foundations. STAF 2017. Lecture Notes in Computer Science(), vol 10748. Springer, Cham. https://doi.org/10.1007/978-3-319-74730-9_25
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DOI: https://doi.org/10.1007/978-3-319-74730-9_25
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